Month: June 2022

In our new ChipChat™ Q&A Series, we’ll be taking you into the lab with one of our expert scientists to see exactly how Organ-Chips are used and why they improve research. In this interview, Emulate Director of Immunology Chris Carman, PhD, discusses our new immune cell recruitment application for the Colon Intestine-Chip and how it can enable researchers to study complex immune response with unprecedented physiological relevance. 

Chris Carman: Our immune system monitors for signs of danger, damage, and infection in the human body. Immune cells travel through the blood stream until they are recruited to enter infected tissue, after which they will respond to the infection, clear it, heal the tissue, and then either die or exit back to the bloodstream. As you can imagine, it is very important that this process be tightly regulated and self-limited; if it weren’t, we’d suffer from all kinds of autoimmune diseases starting at a very early age. So, for the immune system to function properly and to maintain health and homeostasis, the selectivity of immune cell recruitment and response is essential. 

CC: For the vast majority of us, a vast majority of the time, the immune system functions precisely as I just described: recruited immune cells travel to a particular location with a specific purpose. When their job is complete, these immune cells clear out, and the inflammation subsides.  

For those afflicted with inflammatory bowel disease (IBD), however, the process I just described becomes dysregulated, and immune cells are excessively recruited to unintended locations. This causes further dysregulated immune cell recruitment and reactions, triggering a vicious cycle of pro-inflammatory responses that ultimately cause tissue damage and dysfunction, leading to disease. 

The truth is that dysregulated, excessive inflammation is at the heart of all major human diseases. IBD is an excellent example of a disease that depends on, and is ultimately driven by, excessive, dysregulated immune reactions. 

CC: IBD is a complex, chronic disease that is incredibly difficult to study. Its hallmark, the disruption of the epithelial barrier, causes materials inside the intestine, including bacteria, to leak. You can imagine how that drives a subsequent escalation of inflammation as the cycle gets kicked off. What we at Emulate have done in a, frankly, unprecedented manner is model the entire process. As inflammation starts, there is always a priming cue that causes local tissue to undergo changes, including critical pro-inflammatory reprogramming of endothelial cells lining the vessels. Our model begins precisely at this priming step, and it then goes on to capture the full course of the disease progression.  

“The truth is that dysregulated, excessive inflammation is at the heart of all major human diseases. IBD is an excellent example of a disease that depends on, and is ultimately driven by, excessive, dysregulated immune reactions.” 

chris carman, phd

CC: To develop this application, we used the Colon Intestine-Chip, which is a primary human cell model of the colonic barrier that co-cultures organoid-derived epithelium with colon-specific vasculature. We demonstrate in published work that the morphology, function, and transcriptome signature of this model very tightly recapitulate human physiology in a manner that is dependent upon the cell-cell interactions with vascular endothelial cells. This feature is unique to this model compared to competing technologies that lack vasculature, such as organoid-based approaches. 

To initiate inflammation, we applied a well-established cytokine that drives the early IBD progression as the priming stimulus. Critically, we next introduced immune cells—specifically, peripheral blood mononuclear cells (PBMCs)—into the Colon Intestine-Chip’s vascular channel. With this step, our model could capture the complexity of human pathophysiology and was able to recapitulate most of the critical sequence of events for IBD, including immune cell adhesion to the endothelium and migration into the tissue, activation of complex interstitial immune signaling networks, and finally a release of the critical hallmark cytokines and disruption of the epithelial barrier.  

CC: First, a critical aspect of this model is that it represents a more complete and complex recapitulation of both human intestinal physiology and disease. We believe that this unprecedented completeness coupled with experimental tractability will lead to a deeper mechanistic understanding of IBD. Second, and equally as important, we believe this model will enable researchers to identify new therapeutic IBD targets more precisely so that better and more effective therapeutics can be developed and validated. Ultimately, we hope that this model will help researchers greatly diminish the attrition rate of drugs moving into the clinic. 

CC: Traditional models used to study IBD and develop therapeutics for the disease have yielded significant learnings, but they also exhibit important limitations. For example, conventional in vivo studies are almost always performed in mice, which suffer from species-specific differences—a factor that is particularly important for studying the immune system. At the same time, traditional in vitro models involving epithelial cell lines or organoid cultures are highly constrained by their limited complexity. Each of these models has strengths and weaknesses, but they are really only able to look at one piece of the puzzle, and none captures the full complexity of human disease. As such, researchers can only capture a subset of therapeutic targets with these models. Because the Colon Intestine-Chip and immune cell recruitment application capture a more complete sequence of events for IBD, researchers can study a much broader spectrum of disease targets and, subsequently, develop more effective therapeutics. 

CC: In addition to modeling circulating immune cell recruitment, researchers can incorporate so-called resident immune cells—which also play essential roles in driving immune response—into Organ-Chip models. A couple of our developed models apply this functionality today: The Liver-Chip incorporates Kupffer cells to enable studies of immune-mediated toxicity of drug candidates; and the Brain-Chip incorporates microglia to enable studies of neuroinflammation—a process that is implicated in many neurodegenerative diseases, including Alzheimer’s and Parkinson’s disease. 

Researchers at the Wyss Institute have also modeled the immune system by creating a Lymphoid Follicle-Chip, which they have used to recapitulate human immune function and evaluate the efficacy of vaccines for the flu and COVID-19.

CC: Researchers can gain access to these new capabilities in a couple of ways. First, they can work with our in-house service team of experts who can design and execute a study to investigate the efficacy or toxicity of anti-inflammatory drug candidates for IBD. Second, they can bring Emulate Organ-on-Chip technology—which we call the Human Emulation System^®—into their own labs. We offer instrumentation to automate cell culture conditions, Bio-Kits that include the chips and primary human cells customers need to build the Colon Intestine-Chip, and robust protocols, training, and experimental support to help drive success. Whether the research is performed in our labs or in our customer’s labs, our hope is that these new capabilities can enable researchers to develop novel, more effective therapeutics for IBD. 

Read to see why Organ-Chips can help prevent medicines causing drug-induced liver injury from reaching patients

In the beginning, it’s just nausea. But soon, abdominal pain sets in with general fatigue and a growing sense that something has gone wrong. These seemingly innocuous symptoms can be early indications of drug-induced liver injury (DILI). Without quick action, patients developing DILI may progress to multi-organ failure and potentially death.

Bringing harm to a patient is the worst-case scenario that looms large as new drugs transition from preclinical to clinical studies. For more than half a century, DILI has been a frequent cause of post-market drug withdrawal and a common cause of clinical trial failure^1,2. It is unfortunately easy to find examples of this. In January of 2020, the development of inarigavir was halted after the tragic death of patient who presented with clear signs of DILI. This year alone, both Pfizer and Aligos Therapeutics halted production of promising therapeutics as a result of unforeseen DILI in clinical trial patients. It is no exaggeration to say that DILI is a leading patient safety concern.

An insidious condition, DILI develops when a therapeutic turns toxic in a patient’s liver, leading to a decline in liver function and ultimately death. It’s a difficult condition to detect and even harder to predict¹. A battery of preclinical models is used to screen prospective compounds for toxicity before they reach patients, with animal models often viewed as the ultimate predictor of drug safety. Though animal models have undoubtedly played an important role in the evolution of modern drug development, many statistics suggest they are unreliable^2-7:

• 90% of drugs entering clinical trials fail, with approximately 30% failing due to toxicity⁸;
• Toxicity is the primary reason for post-approval drug withdrawal, despite each drug having been declared safe in preclinical animal studies^1,6;
• One study found that, of 43 post-approval drugs with serious toxicity effects, only 19% of them showed direct correlates of toxicity in animal studies, echoing numerous other such studies⁵.

In reviewing the literature, it becomes clear that relying on animal models to predict toxicity generally, and DILI specifically, is unlikely to prevent many toxic compounds from entering clinical trials and causing harm to patients. Such grave errors can be avoided, though, if the right preclinical models are used. 

In a recent study published to Nature Communications Medicine, Emulate researchers provided strong evidence indicating that Organ-on-a-Chip technology can be a far more reliable predictor of drug toxicity.

The predictive power of Organ-on-a-Chip technology

Organ-on-a-Chip technology is a type of microphysiological system in which cells can be cultured in a highly controlled, physiologically relevant microenvironment. These microengineered culture systems combine organ-specific cell types, a tissue-specific extracellular matrix, and biophysical forces to mimic in vivo microenvironments. Multiple studies have shown that cells grown in Organ-Chips closely mimic in vivo cells both in behavior and in gene expression profiles^9-12.

Many studies had previously suggested that Organ-Chips may be superior to conventional preclinical models when predicting drug toxicity^13,14. However, the limited scale of these studies left some doubt about the robustness of Organ-Chips. To truly evaluate the potential of Organ-Chips, a large study was needed.

In December of 2021, such a study was completed by researchers at Emulate⁹.

The research team used 870 Liver-Chips to analyze the model’s ability to predict DILI caused by 27 known hepatotoxic and non-hepatotoxic small molecule drugs. Importantly, these molecules were not chosen at random, but were selected based on guidance from the Innovation and Quality (IQ) Consortium—a collaboration of pharmaceutical and biotechnology companies that aim to advance science and technology to enhance drug discovery programs. Towards this goal, the IQ Consortium has released guidance stipulating basic expectations of preclinical models of liver toxicity. The model should:

• Replicate key histological structures and functions of the liver
• Be able to distinguish between seven pairs of preselected small molecule toxic drugs and their non-toxic analogs
• Demonstrate its ability to predict the clinical responses of six additional selected drugs

Before this study, no microphysiological system had met these standards.

The Emulate Liver-Chip showed close resemblance to the human liver, accurately identified toxic from non-toxic drugs, and correctly predicted toxicity for the tested drugs.

In going beyond the IQ Consortium’s standards, Emulate researchers expanded the study to include an additional 8 known hepatotoxic compounds to evaluate the model’s utility in predictive toxicology.

The Emulate Liver-Chip showed an 87% sensitivity and 100% specificity in predicting drug toxicity, far outperforming liver spheroids (a common preclinical model) which showed a sensitivity of only 47%. Here, it’s worth noting that each of these drugs had been found to be safe in animal models but ultimately proved toxic when given to patients.

The Liver-Chip could save lives and billions of dollars

The mere fact that the Liver-Chip showed an 87% sensitivity and 100% specificity in identifying these toxic drugs is impressive on its own, but set against the history of these drugs, the significance of this improvement falls into sharp relief. The 22 toxic drugs in this study had previously advanced to human use, and collectively are responsible for more than 200 patient deaths and 10 liver transplants¹⁵. Were the Liver-Chip available when these drugs were being developed, many of these deaths could have been avoided.

The benefits of Organ-Chips go beyond improved patient safety. Roughly 75% of costs in drug development are lost to drug candidates that ultimately fail due to efficacy or safety issues¹⁶. A major contributing factor in drug failure is poor model validity. It’s been argued that even small improvements in the predictive validity of preclinical models could have a significant impact on drug development success rates¹⁷.

In the study of the Liver-Chip, Emulate researchers modeled the potential impact that routine use of the Liver-Chip could have on drug development productivity. By simply improving our ability to detect hepatotoxicity with 87% sensitivity, it’s estimated that the Liver-Chip could increase research and development productivity by $3 billion dollars on an annual basis.

Bottom line: The Liver-Chip should be integrated into preclinical development

Emulate’s results provide strong evidence for the use of the Liver-Chip in preclinical drug development. Not only do they faithfully recreate the liver microenvironment, but they’ve proven to be a robust, sensitive, and specific model for assessing a drug’s likelihood of inducing DILI. This means fewer toxic drugs advancing to clinical trials, saving billions of dollars that can be reinvested in other drug candidates, and most importantly, saving patients from the devastating effects of drug-induced liver toxicity.

References

1. Guidance for Industry Drug-Induced Liver Injury: Premarketing Clinical Evaluation Drug Safety. 2009.
2. Babai, Samy, et al. “Safety Data and Withdrawal of Hepatotoxic Drugs.” Thérapie, Feb. 2018, 10.1016/j.therap.2018.02.004. Accessed 18 Mar. 2020.
3. Van Norman GA. Limitations of animal studies for predicting toxicity in clinical trials: Is it time to rethink our current approach? JACC Basic Transl Sci. 2019;4(7):845-854. 2019. doi: 10.1016/j.jacbts.2019.10.008
4. Matthews RA. Medical progress depends on animal models – doesn’t it? J R Soc Med. 2008;101(2):95-98. doi: 10.1258/jrsm.2007.070164
5. Bailey J, Thew M, Balls M. An analysis of the use of animal models in predicting human toxicology and Drug Safety. Altern Lab Anim. 2014;42(3):181-199. doi: 10.1177/026119291404200306
6. Siramshetty VB, Nickel J, Omieczynski C, Gohlke BO, Drwal MN, Preissner R. WITHDRAWN–a resource for withdrawn and discontinued drugs. Nucleic Acids Res. 2016;44(D1):D1080-D1086. doi: 10.1093/nar/gkv1192
7. van Meer PJK, Kooijman M, Gispen-de Wied CC, Moors EHM, Schellekens H. The ability of animal studies to detect serious post marketing adverse events is limited. Regul Toxicol Pharmacol. 2012;64(3):345-349. doi: 10.1016/j.yrtph.2012.09.002
8. Sun, Duxin, et al. “Why 90% of Clinical Drug Development Fails and How to Improve It?” Acta Pharmaceutica Sinica B, Feb. 2022, 10.1016/j.apsb.2022.02.002.
9. Apostolou, Athanasia, et al. “A Novel Microphysiological Colon Platform to Decipher Mechanisms Driving Human Intestinal Permeability.” Cellular and Molecular Gastroenterology and Hepatology, vol. 12, no. 5, 2021, pp. 1719–1741, 10.1016/j.jcmgh.2021.07.004. Accessed 13 Apr. 2022.
10. Si, Longlong, et al. “A Human-Airway-On-a-Chip for the Rapid Identification of Candidate Antiviral Therapeutics and Prophylactics.” Nature Biomedical Engineering, 3 May 2021, pp. 1–15, www.nature.com/articles/s41551-021-00718-9, 10.1038/s41551-021-00718-9.
11. Kasendra, Magdalena, et al. “Duodenum Intestine-Chip for Preclinical Drug Assessment in a Human Relevant Model.” ELife, vol. 9, 14 Jan. 2020, p. e50135, elifesciences.org/articles/50135, 10.7554/eLife.50135. Accessed 17 Feb. 2022.
12. Sheyn, Dmitriy, et al. “Bone-Chip System to Monitor Osteogenic Differentiation Using Optical Imaging.” Microfluidics and Nanofluidics, vol. 23, no. 8, 6 July 2019, 10.1007/s10404-019-2261-7. Accessed 13 Apr. 2022.
13. Danku, Alex Ede, et al. “Organ-On-A-Chip: A Survey of Technical Results and Problems.” Frontiers in Bioengineering and Biotechnology, vol. 10, 10 Feb. 2022, 10.3389/fbioe.2022.840674.
14. Bovard, David, et al. “Organs-On-a-Chip.” Toxicology Research and Application, vol. 1, Jan. 2017, p. 239784731772635, 10.1177/2397847317726351. Accessed 11 Sept. 2019.
15. Ewart, et a. “Performance assessment and economic analysis of a human Liver-Chip for predictive toxicology.” Nature Communications Medicine, 6 Dec. 2022. doi: 10.1038/s43856-022-00209-1.
16. Paul, Steven M., et al. “How to Improve R&D Productivity: The Pharmaceutical Industry’s Grand Challenge.” Nature Reviews Drug Discovery, vol. 9, no. 3, 19 Feb. 2010, pp. 203–214, www.nature.com/articles/nrd3078, 10.1038/nrd3078.
17. Scannell, Jack W., and Jim Bosley. “When Quality Beats Quantity: Decision Theory, Drug Discovery, and the Reproducibility Crisis.” PLOS ONE, vol. 11, no. 2, 10 Feb. 2016, p. e0147215, 10.1371/journal.pone.0147215.